shamindras · shamindras · Jan 27, 2021 · Jan 24, 2021 · Jan 25, 2021 · Jan 25, 2021
diff --git a/NAMESPACE b/NAMESPACE
@@ -8,24 +8,14 @@ export(as_name)
 export(comp_boot_res)
 export(comp_bootstrap_summary)
 export(comp_coef_rwgt)
-export(comp_coef_rwgt_single)
-export(comp_cond_model)
 export(comp_conf_int_bootstrap)
-export(comp_empirical_bootstrap)
-export(comp_empirical_bootstrap_samples)
-export(comp_grid_centers)
-export(comp_multiplier_bootstrap_var)
-export(comp_multiplier_single_bootstrap_var)
-export(comp_sandwich_qr_var)
 export(enquo)
 export(enquos)
 export(expr)
 export(focal_rwgt_var)
 export(focal_slope)
-export(gen_multiplier_bootstrap_weights)
 export(nonlinearity_detection)
 export(qqnorm_bootstrap)
-export(set_ggplot2_theme)
 export(sym)
 export(syms)
 importFrom(Rdpack,reprompt)

diff --git a/R/boot-empirical-var.R → R/boot-empirical.R b/R/boot-empirical-var.R → R/boot-empirical.R
@@ -17,7 +17,7 @@
 #' @return A tibble containing the bootstrap samples (\code{data})
 #'   and their corresponding number (\code{b}).
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -74,7 +74,7 @@ comp_empirical_bootstrap_samples <- function(data,
 #' @return A tibble containing the estimated coefficients (\code{term}) of
 #'   the regressors (\code{term}).
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -164,7 +164,7 @@ comp_cond_model <- function(mod_fit, data, weights = NULL) {
 #'   bootstrapped dataset (\code{m}), the size of the original dataset
 #'   (\code{n}), and the number of the bootstrap repetition (\code{b}).
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'

diff --git a/R/model-diagnostics.R b/R/model-diagnostics.R
@@ -20,8 +20,7 @@
 #'
 #' @return A vector of values corresponding to the centers for the reweighting.
 #'
-#' @export
-#'
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -85,7 +84,7 @@ comp_grid_centers <- function(x, grid_method, n_grid) {
 #'   and estimates of the regression coefficients (\code{term} and
 #'   \code{estimate}).
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -99,7 +98,7 @@ comp_grid_centers <- function(x, grid_method, n_grid) {
 #' y <- 2 + X1 + X2 * 0.3 + stats::rnorm(n, 0, 1)
 #' df <- tibble::tibble(y = y, X1 = X1, X2 = X2, n_obs = 1:length(X1))
 #' mod_fit <- stats::lm(y ~ X1 + X2, df)
-#' boot_samples <- maars::comp_empirical_bootstrap_samples(df, B = 100)
+#' boot_samples <- comp_empirical_bootstrap_samples(df, B = 100)
 #' ols_rwgt_X1 <- comp_coef_rwgt_single(mod_fit, "X1", boot_samples, c(-1, 0, 1, 2))
 #'
 #' # Display the output
@@ -118,7 +117,7 @@ comp_coef_rwgt_single <- function(mod_fit, term_to_rwgt, boot_samples, term_to_r
 
   out <- as.list(1:length(weights_assigned$center)) %>%
     purrr::map_df(~ purrr::map(boot_samples$data,
-      ~ maars::comp_cond_model(
+      ~ comp_cond_model(
         mod_fit = mod_fit,
         data = .x %>% dplyr::mutate(weights = weights_assigned$weights[[.y]][n_obs]) %>%
           dplyr::mutate(weights = weights / sum(weights)),
@@ -235,7 +234,7 @@ comp_coef_rwgt <- function(mod_fit,
     m <- nrow(data)
   }
 
-  boot_samples <- maars::comp_empirical_bootstrap_samples(
+  boot_samples <- comp_empirical_bootstrap_samples(
     data = data %>% tibble::add_column(n_obs = 1:nrow(data)),
     B = B,
     m = m
@@ -252,7 +251,7 @@ comp_coef_rwgt <- function(mod_fit,
   }
 
   out <- terms_to_rwgt %>%
-    purrr::map(~ maars::comp_coef_rwgt_single(
+    purrr::map(~ comp_coef_rwgt_single(
       mod_fit = mod_fit,
       term_to_rwgt = .x[[1]],
       boot_samples = boot_samples,

diff --git a/R/ols-multiplier-boot-var.R → R/ols-boot-multiplier.R b/R/ols-multiplier-boot-var.R → R/ols-boot-multiplier.R
@@ -29,7 +29,7 @@
 #' @return A numeric vector of n (sampled with replacement) random multiplier
 #'   bootstrap weights based on the specified multiplier weights type.
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom Rdpack reprompt
 #' @importFrom rlang .data
@@ -110,7 +110,7 @@ gen_multiplier_bootstrap_weights <- function(n, weights_type) {
 #'
 #' @return A tibble of the bootstrap standard errors.
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -169,7 +169,7 @@ comp_multiplier_single_bootstrap_var <- function(n, J_inv_X_res, e) {
 #'
 #' @return A tibble of the bootstrap calculations.
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom rlang .data
 #'
@@ -204,8 +204,8 @@ comp_multiplier_bootstrap_var <- function(mod_fit, B, weights_type) {
 
   # multiplier weights (mean 0, variance = 1)
   e <- matrix(data =
-                maars::gen_multiplier_bootstrap_weights(n = B * n,
-                                                       weights_type = weights_type),
+                gen_multiplier_bootstrap_weights(n = B * n,
+                                                 weights_type = weights_type),
               nrow = B,
               ncol = n)
 

diff --git a/R/boot-res-var.R → R/ols-boot-residual.R b/R/boot-res-var.R → R/ols-boot-residual.R
diff --git a/R/ols-sandwich-var.R b/R/ols-sandwich-var.R
@@ -13,7 +13,7 @@
 #' @return A tibble containing the sandwich estimator of variance for OLS
 #'   regression.
 #'
-#' @export
+#' @keywords internal
 #'
 #' @importFrom Rdpack reprompt
 #' @importFrom rlang .data

diff --git a/R/ols-boot-summary.R → R/ols-var.R b/R/ols-boot-summary.R → R/ols-var.R
diff --git a/R/scripts_and_filters/replace-keywords-orig.yaml b/R/scripts_and_filters/replace-keywords-orig.yaml
@@ -0,0 +1,16 @@
+"comp_conf_int_bootstrap": "comp_mms_ci_boot"
+"comp_coef_rwgt": "fit_reg_rwgt"
+"focal_rwgt_var": "diag_mms_frwgt"
+"focal_slope": "diag_mms_fslope"
+"nonlinearity_detection": "diag_mms_nldetect"
+"qqnorm_bootstrap": "diag_mms_boot_emp_qqn"
+"get_ggplot2_theme": "set_mms_ggplot2_theme"
+"comp_grid_centers": "comp_mms_grid_cent_rwgt"
+"comp_sandwich_qr_var": "comp_mms_var_sand"
+"comp_multiplier_bootstrap_var": "comp_mms_var_boot_mul"
+"comp_multiplier_single_bootstrap_var": "comp_mms_var_boot_mul_ind"
+"comp_coef_rwgt_single": "fit_reg_rwgt_ind"
+"comp_empirical_bootstrap_samples": "comp_mms_boot_emp_smp"
+"comp_empirical_bootstrap": "comp_mms_boot_emp"
+"gen_multiplier_bootstrap_weights": "comp_mms_mul_boot_wgt"
+"comp_cond_model": "fit_reg"
diff --git a/R/scripts_and_filters/replace-keywords.yaml b/R/scripts_and_filters/replace-keywords.yaml
@@ -1,16 +1,25 @@
-comp_conf_int_bootstrap: "comp_mms_ci_boot"
-comp_coef_rwgt: "fit_reg_rwgt"
-focal_rwgt_var: "diag_mms_frwgt"
-focal_slope: "diag_mms_fslope"
-nonlinearity_detection: "diag_mms_nldetect"
-qqnorm_bootstrap: "diag_mms_boot_emp_qqn"
-set_ggplot2_theme: "set_mms_ggplot2_theme"
-comp_grid_centers: "comp_mms_grid_cent_rwgt"
-comp_sandwich_qr_var: "comp_mms_var_sand"
-comp_multiplier_bootstrap_var: "comp_mms_var_boot_mul"
-comp_multiplier_single_bootstrap_var: "comp_mms_var_boot_mul_ind"
-comp_coef_rwgt_single: "fit_reg_rwgt_ind"
-comp_empirical_bootstrap_samples: "comp_mms_boot_emp_smp"
-comp_empirical_bootstrap: "comp_mms_boot_emp"
-gen_multiplier_bootstrap_weights: "comp_mms_mul_boot_wgt"
-comp_cond_model: "fit_reg"
+# Statistical Utilities - Public Functions
+"comp_conf_int_bootstrap": "comp_ci_boot"
+"comp_coef_rwgt": "diag_fit_reg_rwgt"
+"comp_bootstrap_summary": "comp_boot_summary"
+# Statistical Utilities - Private Functions
+"comp_sandwich_qr_var": "comp_sand_var"
+"gen_multiplier_bootstrap_weights": "comp_boot_mul_wgt"
+"comp_multiplier_single_bootstrap_var": "comp_boot_mul_ind"
+"comp_multiplier_bootstrap_var": "comp_boot_mul"
+"comp_cond_model": "fit_reg"
+"comp_boot_res": "comp_boot_res"
+"comp_empirical_bootstrap_samples": "gen_boot_emp_smp"
+"comp_empirical_bootstrap": "comp_boot_emp"
+"comp_grid_centers": "gen_grid_cent_rwgt"
+"comp_coef_rwgt_single": "diag_fit_reg_rwgt_ind"
+# Diagnostic Utilities - Public Functions
+"focal_rwgt_var": "diag_foc_rwgt"
+"focal_slope": "diag_foc_slope"
+"qqnorm_bootstrap": "diag_boot_emp_qqn"
+"nonlinearity_detection": "diag_nl_detect"
+# Diagnostic Utilities - Private Functions
+# Supporting Utilities - Public Functions
+"get_ggplot2_theme": "set_ggplot2_theme"
+# Supporting Utilities - Private Functions
+"checkargs": "check_fn_args"
diff --git a/R/utils-common.R b/R/utils-common.R
@@ -21,7 +21,7 @@
 #' ("none", "left", "right", "bottom", "top", or two-element numeric vector)
 #'
 #' @return
-#' @export
+#' @keywords internal
 #'
 #' @examples
 #' \dontrun{
@@ -54,8 +54,19 @@ set_ggplot2_theme <- function(ggplot_obj,
 }
 
 
-
-
+#' Check whether the arguments in the function are correctly specified
+#'
+#' \code{checkargs} is used to assess whether the arguments
+#' are correctly specified and returns an error message if
+#' they do not match the correct specification
+#'
+#' @param n Sample size.
+#' @param B Bootstrap repetitions or number of bootstrap samples to be drawn.
+#' @param m Number of observations to be sampled with replacement from the
+#'   dataset for each bootstrap repetition.
+#'
+#' @return
+#' @keywords internal
 checkargs <- function(n = NULL, B = NULL, m = NULL) {
   if (!is.null(B)) {
     assertthat::assert_that(B == as.integer(B),

diff --git a/docs/CONTRIBUTING.html b/docs/CONTRIBUTING.html